/*
 * ------------------------------------------------------------------------
 *
 *  Copyright by KNIME AG, Zurich, Switzerland
 *  Website: http://www.knime.com; Email: contact@knime.com
 *
 *  This program is free software; you can redistribute it and/or modify
 *  it under the terms of the GNU General Public License, Version 3, as
 *  published by the Free Software Foundation.
 *
 *  This program is distributed in the hope that it will be useful, but
 *  WITHOUT ANY WARRANTY; without even the implied warranty of
 *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
 *  GNU General Public License for more details.
 *
 *  You should have received a copy of the GNU General Public License
 *  along with this program; if not, see <http://www.gnu.org/licenses>.
 *
 *  Additional permission under GNU GPL version 3 section 7:
 *
 *  KNIME interoperates with ECLIPSE solely via ECLIPSE's plug-in APIs.
 *  Hence, KNIME and ECLIPSE are both independent programs and are not
 *  derived from each other. Should, however, the interpretation of the
 *  GNU GPL Version 3 ("License") under any applicable laws result in
 *  KNIME and ECLIPSE being a combined program, KNIME AG herewith grants
 *  you the additional permission to use and propagate KNIME together with
 *  ECLIPSE with only the license terms in place for ECLIPSE applying to
 *  ECLIPSE and the GNU GPL Version 3 applying for KNIME, provided the
 *  license terms of ECLIPSE themselves allow for the respective use and
 *  propagation of ECLIPSE together with KNIME.
 *
 *  Additional permission relating to nodes for KNIME that extend the Node
 *  Extension (and in particular that are based on subclasses of NodeModel,
 *  NodeDialog, and NodeView) and that only interoperate with KNIME through
 *  standard APIs ("Nodes"):
 *  Nodes are deemed to be separate and independent programs and to not be
 *  covered works.  Notwithstanding anything to the contrary in the
 *  License, the License does not apply to Nodes, you are not required to
 *  license Nodes under the License, and you are granted a license to
 *  prepare and propagate Nodes, in each case even if such Nodes are
 *  propagated with or for interoperation with KNIME.  The owner of a Node
 *  may freely choose the license terms applicable to such Node, including
 *  when such Node is propagated with or for interoperation with KNIME.
 * ---------------------------------------------------------------------
 *
 * History
 *   31.03.2017 (Adrian): created
 */
package org.knime.base.node.mine.regression.logistic.learner4.sg;

import org.apache.commons.math3.linear.MatrixUtils;
import org.apache.commons.math3.linear.RealMatrix;

/**
 * Contains methods and members that are common to different implementations of the RegularizationUpdater interface.
 *
 * @author Adrian Nembach, KNIME.com
 */
abstract class AbstractPriorUpdater implements RegularizationUpdater {

    private final boolean m_clip;
    private final Prior m_prior;
    private final int m_nRows;

    /**
     * @param prior to use for example a Gauss prior
     * @param nRows the number of rows in the dataset
     * @param clipAtZero flag that indicates whether the influence of the prior is clipped if a coefficient goes to zero
     *
     */
    public AbstractPriorUpdater(final Prior prior, final int nRows, final boolean clipAtZero) {
        m_prior = prior;
        m_clip = clipAtZero;
        m_nRows = nRows;
    }

    protected double clip(final double betaValue, final double normalizedStepSize) {
        // clipping at zero prevents coefficient oscillations around zero
        // and ensures that coefficients can become exactly zero
        double v = betaValue - normalizedStepSize * m_prior.calculate(betaValue);
        if (betaValue < 0) {
            return v < 0.0 ? v : 0.0;
        } else {
            return v > 0.0 ? v : 0.0;
        }
    }

    protected boolean isClip() {
        return m_clip;
    }

    protected double evaluatePrior(final double betaValue) {
        return m_prior.calculate(betaValue);
    }

    protected int getNRows() {
        return m_nRows;
    }

    /**
     * {@inheritDoc}
     */
    @Override
    public RealMatrix hessian(final WeightMatrix<?> beta) {
        int nVar = beta.getNVariables();
        int dim = nVar * beta.getNVectors();
        double val = m_prior.hessianDiagonalValue();
        double[] diag = new double[dim];
        for (int i = 0; i < dim; i++) {
            // intercept term is not regularized
            if (i % nVar == 0) {
                diag[i] = 0.0;
            } else {
                diag[i] = val;
            }
        }
        return MatrixUtils.createRealDiagonalMatrix(diag);
    }

}
